Use of Primary Prevention Implantable Cardioverter-Defibrillators in a Population-Based Cohort Is Associated With a Significant Survival Benefit
Bibliographic record
Abstract
BACKGROUND: Underuse of implantable defibrillators has been previously noted in patients at risk for sudden cardiac death, as well as for survivors of sudden cardiac death. We sought to determine the utilization rates in a primary prevention implantable cardioverter-defibrillator (ICD)-eligible population and mortality in this group compared with a group that had undergone implantation of this therapy. METHODS AND RESULTS: A retrospective cohort of patients from April 1, 2006, to December 31, 2009, was used to define a primary prevention ICD-eligible population. Two groups were compared on the basis of ICD implantation (no-ICD versus ICD). The primary outcome measure was mortality. Of the 717 patients found to be potentially eligible for a primary prevention ICD, 116 (16%) were referred. The remaining cohort of 601 patients were compared with an existing cohort of primary prevention ICD patients (n=290). A significant survival benefit was associated with primary prevention ICD implantation (hazard ratio, 0.46; 95% CI [0.33-0.64]; P<0.0001). When adjusted for prespecified variables known to be associated with overall mortality and propensity score, a similar survival benefit was seen (hazard ratio, 0.59; 95% CI [0.40-0.87]; P=0.01). Appropriate ICD therapy occurred in 26% of those in the ICD group, during a mean follow-up of 2.7 years. CONCLUSIONS: A significant mortality benefit was observed for patients who underwent primary prevention ICD implantation compared with those who did not. Vigilance is required to ensure that patients eligible for primary prevention ICDs are appropriately referred and assessed to allow such patients to benefit from this life-saving therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".